Author: Dann Corbit
Date: 19:57:29 07/12/00
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On July 12, 2000 at 21:57:07, Robert Hyatt wrote: [snip] >I don't see how to do that. The CAP data is composed of _very_ deep searches. >While building a book from millions of games, there is _no way_ to do searching >at each point in the tree. Even at 1 second per search, 2 million games has >something like 160 million moves. Doing 160M 1 second searches will take a >_long_ time. And 1 second is _not_ reliable for choosing book moves. In my 2.4 million games, there are about 150 million positions that have been played. Let's prune back to only consider the 60 million most important. We will build a tree with branches using a variable sized array with a technique similar to that of a skiplist. Only one character needs to be stored for each move forward from the root (the normal chess starting position). We simply sort all possible moves generated and give the number of a given move as an unsigned char from 0 to 255. We will also store a two byte ce, and ebm [extrapolated bm] and bm will require an additional two bytes. A few hundred megabytes will store the entire tree in memory. Certainly less than a gigabyte. A recursive tree walker could propagate window information back up to higher levels. Now, while this won't be the same as a mini-max, we can use the data to narrow the window or tag a choice as definitely wrong. For those that are clearly wrong, we can reevaluate using some other technique. It may also be possible to evaluate the tree using a SQL database. Given a 3090 with a Gig of ram and a few hundred gigs of disk, it might be runnable over a weekend.
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